Environ Resource Econ (2016) 63:687–702DOI 10.1007/s10640-015-9996-8

Incentive-Based Policy Design for Pollution Controland Biodiversity Conservation: A Review

Frans P. de Vries1 · Nick Hanley2

Accepted: 31 December 2015 / Published online: 27 February 2016© The Author(s) 2016. This article is published with open access at Springerlink.com

Abstract This paper provides a succinct review of the main developments in the literatureon incentive-based policy mechanisms in the contexts of pollution control and biodiversityconservation, dating from the early beginnings of the science in the 1960s. A focal point inthe review is on the design features of these policy mechanisms. Key developments in policydesign were originally established in controlling externalities arising from pollution and havesince been extended to policy design tailored towards biodiversity conservation. Specialemphasis is given to the spatial characteristics of the environmental problems underlyingboth pollution control and biodiversity conservation. The paper concludes by drawing somelessons and setting out elements of a future research agenda in both policy domains.

Keywords Environmental policy instruments · Environmental markets ·Mechanism design · Spatial coordination · Conservation auctions

JEL Classification D44 · D82 · Q57 · Q58

1 Introduction

Incentive-based policy instruments have long been argued by economists to be a more effi-cient means of achieving environmental goals such as reductions in polluting emissions andfostering the delivery of ecosystem services (Hanley et al. 2006). Over the last 25years,governments world-wide have begun to make increasing use of policy instruments such as

B Frans P. de Vriesf.p.devries@stir.ac.uk

Nick Hanleyndh3@st-andrews.ac.uk

1 Division of Economics, University of Stirling Management School, Stirling FK9 4LA, Scotland, UK

2 Department of Geography and Sustainable Development, School of Geography and Geosciences,University of St. Andrews, St Andrews KY16 9AL, Scotland, UK

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“green” taxes and tradable pollution permits in an attempt to achieve environmental targets ina more cost-effective manner. One high-profile example is the European Union’s EmissionsTrading System (EU ETS) for carbon emissions. Another is the recently-ended programmeof SO2 credit trading in the U.S. The use of incentive-based policy mechanisms has alsoincreasingly found its way into policy-making in the area of biodiversity conservation andecosystem services delivery. For instance, so-called “payments for ecosystem service” (PES)schemes have been promoted in the EU 2020 Biodiversity Strategy and have also been imple-mented in many EU countries as part of a package of agri-environment schemes. However,applying incentive-based instruments to achieve an improved delivery of ecosystem servicesfrom private land (comprising much of Europe’s forests and almost all of its agriculturalareas) has proved difficult in many cases.

Dating from themillennium ecosystem assessment (MEA2005), the concept of ecosystemservices has dominated public and scientific discussion of the role of “nature” in supportinghuman well-being. Exercises such as TEEB (http://teebweb.org) and the UK NEA (http://uknea.unep-wcmc.org/) have highlighted the types of ecosystem serviceswhich are producedby the functioning of ecosystems and the biodiversity which they contain; how these servicesenhance human well-being, and what their economic value of such benefits might be; andthe factors which explain trends in ecosystem extent and condition over time. The supply ofecosystem services and biodiversity typically goes unrewarded by market forces owing tomissing markets: private landowners usually receive no direct financial reward for enhancingor protecting biodiversity, owing to the non-rivalness and non-excludability of these benefits(Hanley et al. 2006). Indeed, protecting biodiversity typically comes at an opportunity costto landowners—for example, if it requires forgoing profitable land conversion or intensifi-cation. Similar arguments hold for the supply of many ecosystem services. Given the manymarket failures which characterize the supply of ecosystem services and the conservation ofbiodiversity, scholars have investigated the properties of alternative designs of PES schemesto partly correct these market failures (e.g., OECD 2010a; Wünscher et al. 2008; Engel et al.2008; Miteva et al. 2012).

However, the TEEB and UKNEA exercises reveal substantial gaps in our knowledge; notonly over how to value changes in ecosystem services and biodiversity, but also on how to bestdesign effective PES markets (Banerjee et al. 2013; Polasky et al. 2014). This paper attemptsto shed some light on the main lessons we have learnt from the disciplinary perspective ofenvironmental and resource economics.1 We review the key literature on how incentive-basedenvironmental policy can be utilized to encourage the private provision of ecosystem servicesand biodiversity conservation.2 However, we will first present a bird’s eye view of the mainincentive-based mechanisms that have been developed in the context of pollution control,since this was the problem which first shaped economists thinking on the use of incentivesto improve environmental performance in an optimal or a cost-effective manner. Once thisaccount has been established, we aim at showing how such schemes have been “translated”for use in the context of biodiversity protection and conservation.

Given the succinct nature of this review, our paper does not aim to provide an exhaus-tive account of the historical tracks of incentive-based mechanisms in both these domains.However, by sketching the main policy developments over time in the domains of pollutioncontrol and biodiversity conservation, we aim to provide readers with an impression of thecurrent status of the literature in order to draw a future research agenda. In Sect. 2 we willstart by sketching the origins and main developments in incentive-based policy mechanism

1 For an earlier, albeit more comprehensive survey of the literature, see Cropper and Oates (1992).2 See Jack et al. (2008) for an earlier paper reviewing the experience of incentive-based PES schemes.

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for pollution control. Here we will particularly discuss the main properties of (Pigouvian)taxes and tradeable pollution markets, and will try to establish and identify the current sta-tus of these mechanisms. This will serve as a stepping stone for the discussion of the maindevelopments and implementation of incentive-based schemes in the context of biodiversityconservation in Sect. 3. As we will see, this academic discussion has mainly been centredaround the use of payments for biodiversity protection, including the use of conservationauctions. Finally, in Sect. 4 we make some concluding comments and suggest some elementsof a future research agenda.

2 Incentive-Based Mechanisms for Pollution Control3

2.1 Pollution Taxes

The idea of a government introducing a tax or subsidy to correct for the presence of externali-ties is an old one in economics, dating to Pigou’sEconomics ofWelfare in 1920 (Pearce 2002).Market failure as an explanation for environmental problems is even older in economics, origi-nating inMarshall’s discussion ofmarket failure relating to fisheries (Gómez-Baggethun et al.2010). Pigou suggested that governments should introduce a tax, now known as a Pigoviantax, as an optimal tax on a negative externality. He offered the example of air pollutionin Manchester as a case where externalities of production were creating significant damagecosts on society, andwhere such as tax could improve national well-being. However, there aremassive practical and considerable theoretical problems in using such an optimal pollutiontax (Baumol and Oates 1988).

The idea of bargaining solutions to externality problems, associatedwithCoase (1960), haslong been held up as an alternativemeans of attaining the optimal level of pollution. However,this concept runs into difficulties as a practical proposition for environmental policy oncemultiple parties, cumulative pollutants, free riding and moral hazard are considered. Thismeant the field was open to a new and more practical way of pricing pollution.

In the early 1970s, not one but twopractical solutions to the problemof pricing externalitieswere proposed. Baumol andOates (1971) showed that an efficient outcome could be achievedby setting a per-unit tax on polluting emissions. As Baumol and Oates (1988) put it: “A taxrate set at a level that achieves the desired reduction in the total emission of pollutants willsatisfy the necessary conditions for the minimisation of the programme’s cost to society.”All that was required for this to be so was for firms to be cost-minimisers, and for a regulatorto be able to identify and then implement the correct tax rate, given its environmental target,Faced with having to pay a tax, t , on each unit of emissions, the cost-minimizing responsefor a firm is to move along its Marginal Abatement Cost (MAC) curve to the point wheret = MAC. If all firms do this, then marginal abatement costs are equalised across polluters,a necessary condition for achieving the pollution standard (target) at the lowest aggregateabatement cost. The tax rate t is set equal to the shadow price of the emissions target, and isdetermined both by the severity of this target and the position of the aggregate MAC curve.

If regulators face uncertainty about these MAC functions, and thus about the correct taxrate, then they need to iterate onto the correct rate: setting a best-guess tax rate, and thenrevising this rate up or down dependent on the resultant level of emissions relative to thetarget (Baumol 1972). This iterative approach would also be needed where abatement costsare shifting over time, partly due to technological change, and partly due to changes in prices

3 Note that parts of this section draw extensively on chapter 5 of Hanley et al. (2006).

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of inputs and outputs. However, such an approach to tax setting could impose adjustmentcosts on firms (Walker and Storey 1977), and gives forward-looking firms an incentive tobehave strategically, since future tax levels depend on current period emissions for all firms(Karp and Livernois 1994). Experimental studies have recently tried to establish the overallwelfare effects of such dynamic tax models where the regulator is unsure about what tax rateto set (see, for example, Vossler et al. 2013).

The original work by Baumol and Oates described above relates to a “uniformly mixedpollutant”, where damages depend only on aggregate emissions and not their spatial distrib-ution. However, for many potentially polluting substances, ambient concentrations at a givenmonitoring point are dependent not just on the total amount of emissions but their spatiallocation too. Targets set for such pollution problems are likely to be in terms of some ambientmeasure of pollutant concentrations such as NOX and PM10. The implications for the Bau-mol and Oates theorem of a non-uniformly mixed pollutant are that a single tax rate will nolonger be efficient, since the tax rate should vary across sources according to their marginalimpacts on ambient air or water quality levels. Suppose that the ambient level of pollution atany monitoring point j, a j , is a function of emissions from all sources: a j = ∑

k d jkek . Thed jk coefficients are often referred to as “transfer coefficients” where there are k = 1, . . . , Ksources and j = 1, . . . , J monitoring points. In the context of water quality, for example,the transfer coefficient d jk shows the impact of discharges from source k on water qualityat monitoring point j . For non-uniformly mixed pollutants, the regulatory agency’s targetmight be specified as

∑k d jkek ≤ a∗

j , where a∗j is the ambient target at monitoring point

j . The regulator’s problem is now to minimise aggregate abatement costs subject to thisconstraint. In order to achieve an efficient solution, each firm must face a different tax rate,which is determined by that firm’s degradation of environmental quality at each monitoringpoint (given by the transfer coefficients), and by the ambient target itself, i.e., is equal to∑

j d jkμ j for firm j . As Tietenberg (1974, p. 464) argued: “forcing upwind and downwindpolluters to pay the same tax (can) produce the desired concentration (reduction), but ata cost which exceeds the minimum cost means of achieving that concentration.” There areclear links between this finding and the ambient pollution trading idea, which we will discussin more detail below.

Another complication relates to non-point source pollution. If nutrient run-off from farm-land which pollutes waterways is too costly or just impossible to monitor at the farm (source)level, then one cannot tax actual emissions. One alternative is to tax the inputs (such as fer-tilizers), which contribute to this non-point source pollution. Common (1977) first showedthat, so long as the “pollution production function” relating inputs to emissions is known,a desired reduction in emissions can be achieved at least cost by means of a tax on inputs.However, such pollution production functions may be partly stochastic, and may vary spa-tially and over time (Aftab et al. 2007). Input taxes may also involve problems when inputsubstitution occurs if the substitute input has adverse environmental effects.

An alternative tax solution suggested in the literature for non-point source pollution isSegerson’s (1988) ambient tax. This idea addresses the moral hazard aspect of this kindof pollution: if a farmer knows that his emissions cannot be monitored and if emissionsreduction is costly, then there is an incentive to shirk on pollution control. The Segerson taxis composed of two components: a per unit tax or subsidy, which depends on the differencebetween actual ambient levels and the target, and a lump-sum penalty, which is imposedif emissions are too high so that the target is not reached (Hanley et al. 2006, chapter 4).Alternatively, the scheme can be set up as a situation where each firm faces a tax paymentwhich is only positive if ambient pollution exceeds a threshold, andwhere the tax rate dependson the difference between ambient quality and this threshold (Suter and Vossler 2014). The

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threshold for triggering payments can be different from the target level of ambient quality. Alarge literature has since emerged on the conditions under which ambient taxes can achievean efficient outcome. Part of this literature is addressed to the nature of the damage costfunction, and to the extent of abatement options open to the farmer (Horan et al. 1998). Partof it relates to the beliefs of regulators and farmers about the relationship between farm-levelland management and emissions, and ambient pollution levels (Cabe and Herriges 1992).Experimental tests of the consequence of the shape of the damage function, the nature of theambient tax schedule and the degree to which farmers communicate with each other includeSuter et al. (2008), who compare linear with non-linear tax schedules. Other approaches toapplying pricing to non-point pollution include estimated emissions taxes, or subsidies forchanges in land/livestock management or land use.

There are now many examples of Baumol and Oates-type pollution taxes in use in envi-ronmental policy world-wide. These include taxes on inputs, such as fertilizer, pesticide4

and fuel taxes (the latter constituted the biggest single category by value of environmentaltaxes in the OECD in 2010); taxes on estimated emissions, such as CO2 taxes, and taxes onmeasured emissions, such as the Swedish NOX tax on combustion plants and the NOX taxin New South Wales, Australia (OECD 2010b). Within the European Union, environmentaltax revenues are dominated by energy and transport taxes (e.g., on freight transport). Manycountries also tax the disposal of solid wastes to landfill sites. What the European Environ-ment Agency classifies as “environmental tax revenues” have risen slowly in real terms—byaround 19%—since 1995 (EEA 2014). However, no examples exist of the kinds of ambi-ent damage-weighted schemes described above for non-uniformly mixed pollutants, or ofSegerson-type ambient pollution tax schemes. This may possibly be due to the complexityof the former and the perceived unfairness of the latter, since the tax liability of individualsdepends on the actions of others, and not just the pollution due to the actions of that individual.

2.2 Tradeable Pollution Permits

An alternative approach to pollution taxes as away of achieving a target reduction in pollutionat least cost is that of tradeable pollution permits (TPPs). This idea originated with Crocker(1966) and Dales (1968), whilst the original proof of the least-cost property of TPPs is due toMontgomery (1972). Themain idea behind TPPs is to allocate emission rights andmake themtradeable. This results in a market for the right to pollute and consequently in the emergenceof a market price for this right. If the permit market is competitive and all possible gainsfrom trade are realized, this market minimizes the resource costs of achieving a pollutionabatement target. At the outset of the scheme, permits may be issued through grandfatheringor auctioning. In either case, firms are then allowed to trade these permits. We expect firmswith relatively high MACs to be buyers and firm with relatively low MACs to be sellers,assuming that the initial permit allocation is not cost minimizing. In equilibrium, each firmequates the permit price, p∗, with itsMAC schedule. For a uniformly-mixed pollutant this is anecessary condition for individual cost-minimisation across all dischargers. These reactionsby firms move them to their cost-minimising positions and imply differing emission levels(and emission reductions) across firms, just as with a Baumol and Oates tax.

Fowlie and Muller (2013) and Muller and Mendelsohn (2009) discuss the conceptualissues around how to designmarket-based regulation for non-uniformlymixed pollutants, andpresent contrasting empirical results on the net gains from trade with spatial differentiation.These gains from differentiation depend partly on the spatial variation in marginal damage

4 Denmark and Norway have levied environmental taxes on pesticides and fertilisers.

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costs. As these authors note, several alternatives to reflect spatial variations in marginaldamage costs were proposed in the early literature. In an ambient permit system, permitsare denominated in units of damage at receptors. There is a separate market in permits ateach receptor, and firms must trade in as many markets as their emissions affect receptors.Transaction costs would therefore be relatively high.What is more, total emissions can rise asa result of trading, which may cause knock-on environmental problems such as an increase inthe long-range transport of pollutants (Atkinson and Tietenberg 1987). Allowing for spatialvariation in damages can move a permit market closer to the outcome where marginal costsper unit of damage reduction are equalised across sources, but at the expense of a potentialincrease in transactions costs and a fall in the volume of trading.

Using an optimisation model where the regulator seeks to minimise the sum of damageand abatement costs (rather than just trying to hit an arbitrary target), Fowlie and Muller(2013) show that the first-order condition for a socially-optimal allocation of abatementacross sources can be expressed as: c′

i (ei ) /c′j

(e j

) = δi/δ j , where ei and e j are emissionsfrom firm i and j , respectively, and δi and δ j represent the marginal damages associatedwith one unit of emissions from each firm. Thus, in the permit market equilibrium, the ratioof marginal abatement costs must be equal to the ratio of damage costs across space. Eachfirm needs to hold enough permits to validate its emissions as weighted by its own marginaldamage parameter relative to average damages. This outcome can be potentially achieved bydeclaring a matrix of trading ratios which show how many units of emissions reduction froma given source i are equivalent to one unit of emissions from another source j , known asthe “numeraire source” (Muller and Mendelsohn 2009). Muller and Mendelsohn show whatthese trading ratios look like for SO2 emissions from a selection of sources in the UnitedStates, and compare the net effects on welfare of introducing such spatial differentiationinto permit trading ratios. However, despite recognition by the U.S. courts that many existingtradeable permit schemes fail to allow for spatially-varyingdamages, in practice fewexamplesexist of water quality trading markets which use such trading ratios: salinity trading in theHunter River basin, Australia, and phosphorus trading in the Minnesota River being two rareexamples (Fisher-Vanden and Olmstead 2013).

Three other issues have emerged in the literature that are worth noting here. First, animportant consideration is whether firms should be allowed to bank or borrow permits acrossperiods. For instance, a firm could decide to abate more than was required in the presentperiod, earn credits and then bank these for use in a future period, when perhaps it thoughtabatement costs or permit prices would be higher. Allowing the banking of permits hasbeen argued to be desirable since it can even out spikes in permit markets due to suddenincreases in the demand for an output such as electricity (Ellerman et al. 2003); can act asa hedge against uncertainty; and can encourage early reductions in emissions. Cason andGangadharan (2006) found that prohibiting permit banking and borrowing in the laboratoryresulted inmuchgreater price instability, especiallywhen external shocks (e.g., due toweatherevents) are correlated across firms. However, regulators may worry that banking will resultin violations in environmental standards in some time periods. A possible explanation putforward byCason andGangadharan (2006) for this non-compliance is that firmsmay perceivethat benefits can be reaped from under-reporting emissions, so that unused permits can beutilized in future periods.

A second design issue relates to the possibility of allowing trade between point andnon-point sources of pollution. For instance, both point sources (such as industrial plants andsewage treatment works) and non-point agricultural run-off are responsible for severe oxygendepletion in the northern Gulf of Mexico (Ribaudo et al. 2005). Allowing trades betweenthese two source types allows for cost-savings in pollution control, since marginal abatement

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costs for point sources were found to be typically greater than marginal abatement costs fornon-point sources. Simulations showed that a net welfare gain of $46 billion was possiblewith such trading. However, designing a point-nonpoint pollution trading scheme is complex(Shortle and Horan 2008; Stephenson and Shabman 2011).

A third issue is that of whether and how to establish a price floor in a permit market,that is a minimum value below which the market price is not allowed to drop. A recentcriticism of the EU ETS has been that the carbon price has been too low (partly due tothe economic downturn post-2008) to provide a sufficient incentive for firms to invest inlow-carbon technologies (e.g., Burtraw et al. 2010). Price floors can also help to moderateuncertainty over future permit prices (e.g.,Weber and Neuhoff 2010).Wood and Jotzo (2011)set out three mechanisms for establishing a price floor. First, the regulator can commit tobuy permits once the price reaches a certain low level. Second, a reserve price can be usedin permit auctions where sales are not made below this price. Third, a price floor can beestablished by an additional carbon tax operating alongside a permit trading scheme. Priceceilings could also be implemented, if there are fears that permit prices could be “too high”.

Related to this is the problem of permit price volatility. A reserve auction can be usedas an alternative mechanism to a price floor to reduce volatility: the regulator keeps backpart of the total permit supply and then auctions this during periods of tight demand (e.g.,Murray et al. 2009). Price collars, which set a moving ceiling and floor around the currentperiod permit price have also been proposed as a means of mitigating price volatility, withthe regulator stepping into the market to increase or decrease the supply to influence theprice, or to pay subsidies or impose taxes in addition to the permit scheme. Perkis et al.(this issue) study price controls in the laboratory, in particular hard and soft price ceilings.Whilst a hard ceiling does not allow the permit price to rise above an absolute maximumlevel, a soft price ceiling is similar to the reserve auction with a minimum reserve price forpermits (see also Fell et al. 2012). Perkis et al’s study shows that hard ceilings are moreeffective in controlling permit price fluctuations relative to soft price ceilings, in particular inthe case of a reserve auction with a price floor. From a permit market design perspective theresults indicate that hard ceilings would be the preferred mechanism in view of controllingpermit prices. Furthermore, recent evidence from a laboratory experiment by Stranlund et al.(2014) suggests that complementing price controls with permit banking can reinforce pricestability in a market environment where permit price fluctuations are driven by abatementcost uncertainty.

As noted above, tradeable permit markets have become increasingly common for thecontrol of air pollution in both the U.S. and the EU, but also for the management of somewater quality problems in Australia. Efficient permit market design is much simpler forCO2 than is the case for non-uniformly mixed pollutants such as SO2 and NOX, since foruniformlymixed pollutants policy designers do not need toworry about the spatial location ofdischarges (aside from cases of pollution leakage, where emissions move outside the politicalzone of effective control). This may explain the recent surge in carbon trading schemes (e.g.,in California), which has occurred despite claims by some economists that carbon taxes are abetter option (e.g., Goulder andSchein 2013). Forwater pollution, successwith permit tradinghas been much more limited. The smaller number of potential traders in any catchment aswell as the high spatial dependence of damage costs for most water pollution problems maybe important factors here.5

5 See Jones and Vossler (2014) for a laboratory study analysing institutional design features of water qualitycredit trading markets.

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3 Incentive-Based Mechanisms for Biodiversity Conservation

Conservation efforts are often targeted at private landowners, since many valuable ecosystemservices and biodiversity is found on privately-owned land. However, increasing the supplyof ecosystem services and biodiversity typically comes at a cost to these private landowners;for example, in deciding to protect a wetland rather than convert it to pasture, or in fencingnatural vegetation to protect it from grazing. On the other hand, governments—often thebuyers of biodiversity and/or ecosystem services—typically face uncertainty as to how thesecosts are distributed across landowners. Moreover, it is difficult and costly for the buyer tomonitor the actions of landowners if they are offered contracts for undertaking certain landmanagement actions thought to benefit the environment, such as biodiversity enhancement,water quality improvement and reduction of eutrophication (nutrient pollution).

In addition to cost heterogeneity, environmental benefits can also vary spatially acrossland. The heterogeneous nature of both cost and benefits of land use, and the existence ofinformation asymmetries between regulators and landowners, makes it difficult for policy-makers to maximise the net environmental benefits to be delivered by scarce public funds(Hajkowicz et al. 2007), due to problems of adverse selection and moral hazard (Ferraro2008; Fraser 2009; White and Sadler 2012).

This setting poses formidable challenges to the design of policy mechanisms in beingboth effective and efficient in delivering environmental benefits. Economists have becomeincreasingly interested in how to incentivize private landowners to change their behaviour inorder to increase the supply of environmental goods and ecosystem services (see Engel et al.2008). Throughout the European Union, agri-environmental PES schemes have involved thevoluntary opt-in of farmers, who, in return for undertaking a range of management actions,receive fixed payments on a per-hectare basis for land enrolled (Hanley et al. 2012). However,the inherent problem underlying such uniform payment schemes is adverse selection, imply-ing that payment levels might not relate to the actual costs of participation for individuallandowners, who are over-compensated for their participation due to a lack of information onthe part of the regulatory agency regarding the opportunity costs of participation. Moreover,uniform payment schemes may also not enroll those farmers or landowners who can deliverthe greatest environmental benefits.

The challenge of revealing landowners’ real opportunity costs, in conjunction withattempts to find ways to increase the environmental benefits delivered by participation,has resulted in significant advances in the area of policy design in the last two decades.As mentioned before, maximizing environmental benefits whilst at the same time enhancingparticipation of farmers given the inherent differences in their opportunity costs is key in viewof constrained public funds. An important incentive-based mechanism that can potentiallydeal with this problem is the conservation auction. Seminal work by Latacz-Lohmann andVan der Hamsvoort (1997, 1998) showed that auctions can potentially deal with the issuesof adverse selection and lack of cost-effectiveness by promoting price competition amongstlandowners for the supply of non-marketed goods. In conservation auctions, landowners ten-der bids to a regulatory agency (or some other buyer such as a conservation organizationor water company) indicating their minimum willingness to accept compensation for under-taking specified conservation actions. The regulatory agency offers conservation contractsto those bidders whose asking price —weighted by the expected environmental benefits oftheir actions—is most cost-effective first, taking on higher and higher bidders up to somebudget constraint or environmental target. Competition with other bidders gives landown-ers an incentive to moderate their bids, although the fact that the (opportunity) cost of the

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environmental action is unobservable to the government allows landowners to still earn aninformation rent (Rolfe and Windle 2011).

Cason and Gangadharan (2004) test-bed the basic conservation auction in the laboratory.In one of the treatments they vary the auction’s information structure by revealing the potentialbenefits of conservation projects to sellers (landowners). Interestingly, relative to a treatmentwithout providing this information, the overall performance of the auction decreases underthe “full” information treatment. The authors argue that this is due to sellers’ less accuraterepresentation of the opportunity costs for projects exhibiting high benefits.6 The findingthat information concealment about potential conservation benefits can lead to more efficientauction performance has recently also been confirmed theoretically by Glebe (2013). Glebe’sstudy also demonstrates that revealing such information may attract landholders and can thuslead to higher participation rates in the auction, hence making the market “thicker”, an issueto which we will come back later.

Cason and Gangadharan (2004) further show that the pricing rule matters for auctionperformance, by comparing a uniform price auction with a discriminatory price auctionwhere successful sellers are paid a contract sum equal to their bid. Their experiment revealsthat a conservation auction based on a uniform pricing rule results in some sellers beingover-compensated relative to their actual opportunity costs. This result is similar in spiritto the aforementioned inefficiency resulting from a fixed-rate payment scheme (e.g., on aper-hectare basis) as applied in many EU agri-environment schemes. As a result, overallauction performance is improved with a discriminatory pricing rule where the actual price isoffered to individual successful sellers. A similar experimental finding is derived in Casonand Gangadharan (2005) where a uniform price auction is compared with a discriminatoryprice auction in a context of non-point source pollution. In their experiment a discriminatoryauction tends to deliver reductions in non-point source pollution problems more efficientlythan a uniform price auction.7

Schilizzi and Latacz-Lohman (2007) extend this work by testing experimentally how adiscriminatory price conservation auction compares with an equivalent fixed-rate paymentmechanism through the lens of cost-effectiveness, information rents, and economic efficiency.They do so by distinguishing two auction formats: a budget-constrained auction and a target-constrained auction. In the former auction type the budget is fixed and given but the target(outcome) uncertain; in the target-constrained auction the outcome is predetermined butsubject to cost uncertainty. In a static (one-period) market setting the experimental evidenceindicates that both auction formats are superior to the fixed-rate payment scheme in terms ofoverall performance. However, in a dynamic setting the auction’s dominance over the fixed-rate scheme reduces. This means that when sellers have the opportunity to learn from pastdecisions and can update their bidding behavior, fixed-rate payment schemes can perform aswell as an auction mechanism.

More recent experimental analyses by Arnold et al. (2013) on budget-constrained dis-criminatory auctions for conservation reveal that this mechanism may not be able attract thefull set of potential bidders (landowners), implying that auctions can actually induce adverse

6 See Cason et al. (2003) for a more detailed description of the experimental design in the context of non-pointsource pollution resulting from agricultural land management, such as fertiliser run-off from fields.7 Note that this research does not take into account compliance monitoring. In reality monitoring compliancein agri-environment schemes is often imperfect, resulting in reduced incentives for (some) landholders tocomply with land management changes. This can undermine the delivery of conservation benefits and couldlead to reduced cost-effectiveness of the auction mechanism. In an experimental study, Kawasaki et al. (2012)find evidence indicating that, in situations where monitoring landholder compliance is imperfect, the uniformprice auction results in overall greater efficiency than the discriminatory price auction.

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selection. This, in turn, can undermine the potential supply of ecosystem services and biodi-versity from land. Contrasting the auction institution with screening contracts, they furthershow by means of laboratory experiments that such contracts may outperform auctions interms of social welfare. However, in a dynamic auction experiments where bidders can enterand submit offers in any period, Fooks et al. (2015) show that such auction institutions aremore efficient relative to a no-auction baseline. This result could imply that dynamic conser-vation auctions with endogenous entry may result in “bidder selection” over time and inducebidders to sort themselves into different types. In this respect, allowing for endogenous entryseems to be an interesting design feature which is of relevance for real markets, as this couldpotentially mitigate the adverse selection problem identified by Arnold et al. (2013).

Although competition amongst bidders in conservation auctions can lead to improved cost-effectiveness, Rolfe et al. (2009) present results from a conservation auction implementedin an Australian field experiment to study how extending the usual single round auctionto a multiple bidding round auction affects performance. Their study shows that such anextension allows landowners to learn and obtain more information during the auction. Thisis conducive to reducing overall strategic uncertainty, which subsequently leads to a moreefficient outcome. An iterated (multi-round) conservation auction has also been studied byReeson et al. (2011), but with the additional design feature of a variable, unknown endperiod of the auction. This revealed two results. The first is that, over time, bidders canobserve the location of the other bidders in the landscape. The ability to “observe” bidsreduces uncertainty, which is conducive to steering spatial coordination of land managementactions. Secondly, not knowing when the auction ends reduces rent seeking behaviour as itencourages subjects to bid more modestly in earlier rounds given subjects will not be able torevise bids downward from an initial high bid once the auction has ended. Although the studyby Reeson et al. (2011) shows that coordination of landowner behaviour can be “steered” inthe laboratory, these kinds of auctions are still relatively rare in practice. Actual conservationauction schemes have generally placed relatively little focus on the spatial coordination oflandowner participation in order to improve delivery of biodiversity and ecosystem servicesacross land. This is because implementing auctions with explicit spatial coordination ischallenging.

Considerable experience in designing and implementing conservation auctions now existsinAustralia, and analysis shows that facilitating sufficiently high levels of participation is cru-cial to scheme performance, as is the design of the environmental metric used to weight bids(Williams et al. 2012). Key features impacting on participation included length of contract,complexity of legal agreements, payment schedule, monitoring requirements and communi-cation with potential bidders (Whitten et al. 2013).

An alternative price-based policy instrument that accounts for the dependency betweenconservation benefits and spatial connectivity of land parcels is the agglomeration bonus(Parkhurst et al. 2002; Parkhurst and Shogren 2007). This scheme offers additional paymentto landowners who voluntarily enroll parcels of landwhich lie next to neighbours’ landwhichis also offered for enrolment. Parkhurst et al. (2002) show that this mechanism inherentlyfeaturesmultipleNash equilibriawhich can ranked in termsof the amount of habitat protected,the expected returns to landowners, and net social benefits. Test-bedding the agglomerationbonus in the laboratory, the authorsfind that habitat fragmentation can significantly be reducedrelative to a no-bonus benchmark. Indeed, the experimental results show that subjects wereoften able to coordinate on the efficient (contiguous) land reserve. Parkhurst and Shogren(2007) subsequently incorporate a more explicit spatial target into the basic agglomerationbonus scheme. Laboratory evidence indicates that the agglomeration bonus is still able tofoster coordination of land management actions but can be more effective depending on the

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type of land reserve targeted (for instance, a corridor style habitat or a single core habitatstyle).

Banerjee et al. (2012) extend this seminal work by examining how spatial coordination isfostered under an agglomeration bonus schemes by varying the group size of subjects (who actas landowners) in a laboratory experiment. They implement a simple (fixed) circular networkstructure but as main treatment vary the size of the network (i.e., different number of farmsin the neighbourhood) in order to test its impact on spatial coordination of landowners andthe scheme’s effectiveness in generating environmental benefits. The experiment indicates asignificant difference in patterns of coordination between groups. In particular, coordinatingland management actions is more difficult in the larger network compared to the smallernetwork. Using a similar kind of network structure but without varying the network size,Banerjee et al. (2014) also identifymultipleNash equilibria in the experimental agglomerationbonus scheme, which can lead to coordination failure by not reaching the socially optimalland configuration.However, they show that the information structure available to landholdershas implications for the success of the scheme in delivering environmental benefits in thatrevealing the landmanagement choices of a subject’s direct and indirect neighbours enhancesthe ability to coordinate to the Pareto dominant equilibrium. The policy message is clear:fostering market transparency by revealing landowners’ land management actions is likelyto improve the environmental outcome in terms of higher conservation benefits generatedfrom spatial connectivity and spatial spillovers.

Whilst this research on the agglomeration bonus mechanism is a promising start, currentlimitations include the treatment of heterogeneity in landowner and environmental character-istics, and the assumption of common knowledge of payoffs. Perhaps most importantly, thecurrent understanding of the agglomeration bonus does not deal with the adverse selectionor (cost) in-efficiency problems since no auction mechanism is used to decide participation.Given this limited degree of landholder participation, these markets can be relatively “thin”.A novel incentive mechanism developed by Parkhurst et al. (this issue) to simultaneouslyaddress the issue of landholder heterogeneity and to create a thicker market for habitat con-servation is called Tradable Set Aside Requirements (TSARs). It builds on the concept oftradeable development rights (habitat/conservation banking), similar in spirit as a market fortradeable pollution permits as discussed in the previous section. The main difference with anagglomeration bonus is that TSARs create an explicit market environment where buyers andsellers can trade conservation. Parkhurst et al. test-bed the TSARs mechanism both with andwithout an agglomeration bonus. The experimental results overall reveal that TSARs are gen-erally effective in improving the spatial connectivity of habitat. However, when combiningTSARs with an agglomeration bonus, the experimental results reveal a trade-off. While onthe one hand the environmental effectiveness increases due to enhanced habitat connectivity,the costs are higher compared to the treatment with a TSARs mechanism only.

Two important features highlighted in the aforementioned policy mechanisms is the desir-ability to foster spatial coordination and allowing for competition between potential suppliers.Yet jointly achieving these objectives is difficult due to a tension between information pro-vision, cooperation and competition. One way forward is to explore spatially-differentiatedconservation auctions. However, to enhance environmental outcomes by fostering the con-tiguity of landholdings, cooperation rather than competition between landowners wouldlikely be much more effective, since cooperation between neighbouring landowners directlyincreases spatial coordination (Windle et al. 2009). So far the existing literature on conser-vation auctions typically assumes that bids from landowners are independent. That is, thecurrent generation of conservation auctions do not address the issue of spatial coordinationand do not incorporate the potential synergies across landowners. However, recently Banerjee

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et al. (2015) built spatially adjacent land use management into a conservation auction andtested it in the laboratory as to how information about the regulator’s spatial objective impacton subjects’ bidding behavior and subsequent auction performance. Interestingly, althoughdisclosing information about the spatial features increases rent seeking among participants,the auction’s overall efficiency is unaffected.

4 Conclusion and Directions for Future Research

This paper has provided a brief overview of the main economic incentives which have beendeveloped to reduce pollution, to increase the supply of desirable ecosystem services and toenhance biodiversity conservation.Much of the early literature in pollution control economicsfocused on the problems of efficiently regulating point source emissions of local and regionalair and water pollutants, which reflected the dominant environmental concerns of the 1970s.Increasingly, the focus of the literature has moved to non-point source pollution (which isnow the main cause of low ecological quality in many European and U.S. water bodies) andto the design of pollution control instruments as part of climate change policies, with thefast growth of (regional) CO2 markets being particularly important. Price collapses and pricevolatility in the carbon market have also promoted recent work on improving the functioningof permit markets, along with developing a broader understanding of what motivates firmswith regard to their environmental choices rather than the simple cost-minimisation strategiesof the early literature. Finally, a literature is emerging on the optimal design of pollution taxeswhen options exist about how to define the tax base (emissions, inputs, outputs) and howmuchto differentiate taxes across sectors when administrative and abatement costs differ acrosssectors and policy choices (Shortle et al. 1998; Smulders and Vollebergh 2015). This involvesa balancing of the gains and losses of greater complexity in policy design for pollution taxes,which has parallels in the Payment for Ecosystem Services (PES) literature with work byArmsworth et al. (2012).

Indeed, a large body of work now exists on how best to design PES schemes and incentiveswhich assist in biodiversity conservation. Here, attention is rather on the interaction of onebuyer (typically a government or conservation agency) with multiple potential sellers whocan increase the supply of such environmental goods by changing how they manage land.One can think here of three main areas of research that still need further investigation.

The first relates to the use of conservation auctions. As has been clear since the late 1990s,auctions have the potential to achieve considerable gains in efficiency in achieving environ-mental goals such as restoring native vegetation or reducing non-point source pollution fromfarmland. A considerable degree of practical experiencewith implementing such auctions hasnow been attained, mainly in Australia and the United States. However, there are a numberof design and implementation issues which require more thought. One is that of achievingspatial coordination in auctions (Windle et al. 2009), which implies the need for coordinationamongst bidders (e.g., if group bids are rewarded). But this then raises a problem over howto deal with collusion amongst bidders, since this can lead to the erosion of cost savingsover time. For instance, Calel (2012) studies how a joint bid of a group of landholders canbe integrated into a conservation auction. Although he finds that coordination of landholderaction is improved, auction efficiency is reduced. The second design issue relates to the levelof design complexity and the transactions costs of auctions (increasing complexity can deterparticipation). Another design issue relates to bundling of ecosystem services and biodiver-sity conservation, whereby bidders offer multiple environmental goods for a single price.

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We are not aware of any existing conservation auctions with this feature. However, perhapsa worthwhile route to explore is to design auctions by drawing upon features of the HigherLevel Stewardship scheme in the UK, where farmers have to offer multiple environmentalimprovements on their farm or land in return for a higher payment.

A second avenue of research which is needed relates to the design of conservation sub-sidies (as distinct from auctions). Some papers are starting to emerge on the properties ofcontracts which pay for environmental outcomes rather than management actions and forcontracts which pay for a mix of actions and outcomes (Derissen and Quaas 2013;White andHanley, this issue). Paying for environmental outcomes incentivises farmers to produce suchoutcomes more efficiently, exploits the private information they hold on species distributionsand abundance on their land, and avoids the regulator having to monitor hard-to-observeinputs such as conservation effort. However, outcome-based payments transfer risk onto thefarmer and imply costs for measuring environmental outcomes.

A third field of useful future research will lie in the closer integration of ecological mod-elling and ecological indicators with the design of PES-type incentives. Since the aim of suchincentives is to increase the supply of environmental goods, understanding how this supply isrelated to changes in land use and land management is key. Examples include understandingthe spatial variability in ecological response across species to changes in land management(Armsworth et al. 2012); or the ecosystem production function which generates economicbenefits, an example being the interactions between wild and commercial pollinators withtheir ecosystems and with food crops (Ehmke et al. 2015). Environmental metric designhas also been argued to be key to explaining the relative success or failure of conservationauctions (Williams et al. 2012), but little effort has been made so far in including the proper-ties of environmental metrics in the optimal design of economic incentives for biodiversityconservation or ecosystem service supply.

Acknowledgments The research reported here is derived from work conducted under the Eco-Deliveryproject (http://www.eco-delivery.stir.ac.uk/). We are grateful to the European Investment Bank (EIB) forfinancial support through their EIB-University Research Action Programme (theme Financial and EconomicValuation of Environmental Impacts). The findings, interpretations and conclusions presented are entirelythose of the authors and should not be attributed in any manner to the EIB. Any errors remain those of theauthors. We thank an anonymous referee for helpful comments on an earlier version.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 Inter-national License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution,and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source,provide a link to the Creative Commons license, and indicate if changes were made.

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